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大语言模型+智能评价的“双智”赋能现代工科微生物学混合式课程教学研究与实践
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陕西省重点研发一般项目(2022GY313);陕西省高等教育教学改革研究重点项目(23ZZ016);陕西省教师教育改革与教师发展研究重点项目(SJS2023ZD012);陕西省研究生教育教学改革重点项目(YJSZG2023039);陕西省学位与研究生教育研究项目(SXGERC2023042);西安电子科技大学基本科研业务费项目(ZYTS24158)


Research and practice on the blended teaching of Modern Engineering Microbiology empowered by large language model and intelligent evaluation
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    摘要:

    教育数字化转型背景下的高等教育呈现出多元化、个性化和智能化的发展趋势,传统的教学模式已不能完全满足学生的多样化学习需求。现代工科微生物学课程结合西安电子科技大学电子信息学科优势,以培养具备跨学科创新型电子信息特色生物医学工程优秀人才及未来领军人才为主要目标,具有很强的应用导向性、学科交叉性和深度挑战性,在当今人工智能+教育背景下,深度融合人工智能手段开展教学改革工作的重要性不言而喻。本文通过对我校生物医学工程专业本课程的混合式教学实践情况,重点探讨了基于大语言模型的人机协同学习模式与团队自主研发全过程深度网络智能评价模型在课程设计和教学过程中的应用。一方面鼓励学生科学利用AI技术辅助学习,通过基于大语言模型的人机协同学习模式,充分发挥人工智能技术在辅助教学中的作用。学生与其进行互动式学习,获取所需知识和反馈,提高学习效率。同时,基于全过程智能评价平台发挥引导和监督作用,确保学习质量。研究实践结果表明该教学模式有效提升了教与学的质量和效果,为数字化转型背景下的高等教育课程改革实践提供了一定的范式和经验。

    Abstract:

    Under the background of digital transformation in education, higher education presents a trend of diversification, personalization, and intelligence. Conventional teaching models cannot fully meet the diverse learning needs of students. Modern Engineering Microbiology, as a course leveraging the strengths of the discipline of electronics and information at Xidian University, aims to cultivate outstanding interdisciplinary and innovative talents in biomedical engineering with a distinctive electronic information character, as well as future leaders in the field. The course is application-oriented, interdisciplinary, and challenging in depth. In the current context of artificial intelligence (AI)+education, it is of great significance to integrate AI into the teaching reform. We investigate the blended teaching practice of this course for the students majoring in biomedical engineering at Xidian University, with focus on the application of human-machine collaborative learning based on the large language model and the team’s self-developed deep network intelligent evaluation model throughout the entire process in course design and teaching process. We encourage students to utilize AI to assist learning and fully leverage the role of AI in assisted teaching. The human-machine collaborative learning model enables the interactive learning of students, who can obtain the necessary knowledge and feedback and thus improve the learning efficiency. At the same time, the intelligent evaluation platform throughout the entire process plays a guiding and supervisory role to ensure the quality of learning. The research and practice results indicate that this teaching model improves the quality and effectiveness of teaching and learning, providing a paradigm and experience for the reform of higher education curriculum in the context of digital transformation.

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谢晖,朱守平,刘鹏,陈雪利. 大语言模型+智能评价的“双智”赋能现代工科微生物学混合式课程教学研究与实践[J]. 微生物学通报, 2025, 52(1): 445-456

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  • 收稿日期:2024-04-15
  • 录用日期:2024-05-30
  • 在线发布日期: 2025-01-21
  • 出版日期: 2025-01-20
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